techtimes

Open-Source Coding Model Ornith-1.0 Writes Its Own Training Scaffold in Reinforcement Learning

DeepReinforce today released Ornith-1.0, a family of open-source coding models built around a mechanism most RL-trained agents avoid: the model itself writes the training harness that guides its own ...

Small Language Models Outperform Frontier AI On Cost, Speed And Accuracy

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — and save money.

Beckhoff's TwinCAT CoAgent Accelerates Automation Programming with Built-In AI Tools

TwinCAT CoAgent delivers powerful AI-assisted engineering and programming support across every stage of the automation ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Tech Xplore

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...
Medical Device and Diagnostic Industry (MD+DI)

The AI Era: How Deep Learning is Overcoming Data Scarcity in Medical Imaging

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
Nature

An autoencoder driven deep learning geospatial approach to flood vulnerability analysis in the upper and middle basin of river Damodar

Flood vulnerability mapping has significantly progressed with the advent of Machine Learning (ML), bringing greater certainty to predictions. However, conventional supervised ML techniques may not be ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
IEEE

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach

Several domains increasingly rely on machine learning in their applications. The resulting heavy dependence on data has led to the emergence of various laws and regulations around data ethics and ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...